Update app.py

app.py

@@ -20,9 +20,9 @@ client = Groq(api_key=os.getenv("GROQ_API_KEY"))
 
 TRANSCRIPTION_MODEL = "whisper-large-v3-turbo"
 CHAT_MODEL = "llama-3.3-70b-versatile"
+MAX_VIDEO_DURATION = 120  # 2 minutes in seconds
 
-MAX_VIDEO_DURATION = 120  # 2 minutes
-
+# Job Matching Weights
 SCORING_WEIGHTS = {
     "technical_skills": 0.30,
     "soft_skills": 0.20,
@@ -63,158 +63,55 @@ def transcribe_video(video_file_path, output_language="English"):
             )
         transcript_text = transcription.text
         confidence = 0.95
-        segments = []
-        if hasattr(transcription, 'segments') and transcription.segments:
-            confidences = []
-            for segment in transcription.segments:
-                if hasattr(segment, 'confidence'):
-                    confidences.append(segment.confidence)
-                elif hasattr(segment, 'avg_logprob'):
-                    confidences.append(min(1.0, max(0.0, 1.0 + segment.avg_logprob)))
-            if confidences:
-                confidence = sum(confidences) / len(confidences)
-            for seg in transcription.segments:
-                segments.append({
-                    "start": getattr(seg, 'start', 0),
-                    "end": getattr(seg, 'end', 0),
-                    "text": getattr(seg, 'text', "")
-                })
-        return {
-            "transcript": transcript_text,
-            "confidence": confidence,
-            "duration": duration,
-            "segments": segments,
-            "language": getattr(transcription, 'language', 'en')
-        }
+        return {"transcript": transcript_text, "confidence": confidence, "duration": duration}
     except Exception as e:
-        error_msg = (f"Transcription failed: {str(e)}" if output_language == "English" else f"ٹرانسکرپشن ناکام: {str(e)}")
-        print(f"Transcription error: {str(e)}\n{traceback.format_exc()}")
+        error_msg = "Transcription failed: " + str(e) if output_language=="English" else "ٹرانسکرپشن ناکام: " + str(e)
         return {"error": error_msg}
     finally:
         if audio_path and os.path.exists(audio_path):
-            try: os.unlink(audio_path)
-            except: pass
-
-# ============================================================================
-# ANALYSIS MODULE
-# ============================================================================
-
-def get_system_prompt(language):
-    if language == "English":
-        return """You are an expert HR professional and career counselor specializing in graduate recruitment. Provide structured, JSON-formatted insights."""
-    else:
-        return """آپ گریجویٹ بھرتی میں ماہر HR پروفیشنل ہیں۔ JSON فارمیٹ میں تجزیہ فراہم کریں۔"""
-
-def create_analysis_prompt(transcript, language):
-    if language == "English":
-        return f"""Analyze the candidate's transcript and provide JSON analysis.\n{transcript}"""
-    else:
-        return f"""امیدوار کے ٹرانسکرپٹ کا تجزیہ کریں اور JSON فارمیٹ میں تجزیہ فراہم کریں۔\n{transcript}"""
-
-def analyze_candidate(transcript, output_language="English"):
-    try:
-        prompt = create_analysis_prompt(transcript, output_language)
-        completion = client.chat.completions.create(
-            model=CHAT_MODEL,
-            messages=[
-                {"role": "system", "content": get_system_prompt(output_language)},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.4,
-            max_completion_tokens=2048,
-            stream=False
-        )
-        response_text = completion.choices[0].message.content
-        return parse_analysis_response(response_text, output_language)
-    except Exception as e:
-        error_msg = (f"Analysis failed: {str(e)}" if output_language == "English" else f"تجزیہ ناکام: {str(e)}")
-        print(f"Analysis error: {str(e)}\n{traceback.format_exc()}")
-        return {"error": error_msg}
-
-def parse_analysis_response(response_text, language):
-    try:
-        start_idx = response_text.find('{')
-        end_idx = response_text.rfind('}') + 1
-        if start_idx != -1 and end_idx > start_idx:
-            return json.loads(response_text[start_idx:end_idx])
-        else:
-            return {"candidate_summary": response_text}
-    except:
-        return {"candidate_summary": response_text}
+            try:
+                os.unlink(audio_path)
+            except:
+                pass
 
 # ============================================================================
-# JOB MATCHING MODULE
+# SIMPLE UI
 # ============================================================================
 
-def match_jobs(analysis_result, output_language="English"):
-    fallback = [{"title": "Business Analyst", "score": 78, "explanation": "Good fit"}]*10
-    return fallback
-
-# ============================================================================
-# REPORT GENERATION
-# ============================================================================
-
-def generate_report(transcript, analysis, job_matches, confidence, language):
-    report = f"Developer: Najaf Ali Sharqi\n"
-    report += f"Transcript Confidence: {confidence:.2%}\n\n"
-    report += f"Candidate Summary:\n{analysis.get('candidate_summary', 'N/A')}\n\n"
-    report += "Top 10 Job Matches:\n"
-    for job in job_matches[:10]:
-        report += f"- {job['title']} (Score: {job['score']})\n"
-    report += f"\nTranscript:\n{transcript}\n"
-    return report
-
-# ============================================================================
-# PROCESSING PIPELINE
-# ============================================================================
-
-def process_video(video_file, output_language):
-    if video_file is None:
-        return "", "", "", "", "", "Please upload a video."
-    transcription_result = transcribe_video(video_file, output_language)
-    if "error" in transcription_result:
-        return "", "", "", "", "", transcription_result["error"]
-    transcript_text = transcription_result.get("transcript", "")
-    confidence = transcription_result.get("confidence", 0)
-    analysis_result = analyze_candidate(transcript_text, output_language)
-    job_matches = match_jobs(analysis_result, output_language)
-    final_report = generate_report(transcript_text, analysis_result, job_matches, confidence, output_language)
-    return transcript_text, str(analysis_result), str(analysis_result.get('candidate_summary','')), str(job_matches), final_report, ""
-
-# ============================================================================
-# GRADIO UI
-# ============================================================================
+def process_video_ui(video, language):
+    lang = "English" if "English" in language else "Urdu"
+    if not video:
+        return "", "Please upload a video file." if lang=="English" else "براہ کرم ایک ویڈیو فائل اپ لوڈ کریں۔"
+    
+    result = transcribe_video(video, lang)
+    transcript = result.get("transcript", "")
+    error = result.get("error", "")
+    
+    return transcript, error if error else "✅ Success / کامیاب"
 
 def create_ui():
     with gr.Blocks(title="AI Graduate Job Matcher") as demo:
-        gr.HTML("<h1>🎓 AI Graduate Job-Matching Platform</h1><h3>Developer: Najaf Ali Sharqi</h3>")
-        video_input = gr.Video(label="Upload Video / ویڈیو اپ لوڈ کریں")
+        gr.HTML("<h1>🎓 AI Graduate Job-Matching Platform</h1><p>Developer: Najaf Ali Sharqi</p>")
+        video_input = gr.Video(label="Upload Video / ویڈیو اپ لوڈ کریں", source="upload")
         language_dropdown = gr.Dropdown(choices=["English", "Urdu / اردو"], value="English", label="Output Language / آؤٹ پٹ زبان")
-        process_btn = gr.Button("🚀 Generate Report / رپورٹ بنائیں")
-        transcript_output = gr.Textbox(label="Transcript")
-        skills_output = gr.Textbox(label="Skills")
-        summary_output = gr.Textbox(label="Summary")
-        jobs_output = gr.Textbox(label="Job Matches")
-        report_output = gr.Textbox(label="Complete Report")
-        error_output = gr.Textbox(label="Status / حیثیت")
-        
-        def run_pipeline(video, language):
-            lang = "English" if "English" in language else "Urdu"
-            return process_video(video, lang)
+        process_btn = gr.Button("🚀 Generate Transcript / ٹرانسکرپٹ بنائیں")
+        transcript_output = gr.Textbox(label="Transcript / ٹرانسکرپٹ", lines=15)
+        status_output = gr.Textbox(label="Status / حیثیت", lines=1)
         
         process_btn.click(
-            fn=run_pipeline,
+            fn=process_video_ui,
             inputs=[video_input, language_dropdown],
-            outputs=[transcript_output, skills_output, summary_output, jobs_output, report_output, error_output]
+            outputs=[transcript_output, status_output]
         )
+    
     return demo
 
 # ============================================================================
-# MAIN ENTRY POINT
+# MAIN
 # ============================================================================
 
 if __name__ == "__main__":
     if not os.getenv("GROQ_API_KEY"):
-        print("⚠️ GROQ_API_KEY not found!")
+        print("⚠️ WARNING: GROQ_API_KEY not found!")
     demo = create_ui()
-    demo.launch(server_name="0.0.0.0", server_port=7860, share=False)
+    demo.launch(server_name="0.0.0.0", server_port=7860)